Predicting the future state of a mobile device user

ABSTRACT

In one embodiment, a computing system receives an indication of current mobile device usage by a user. The user is also associated with one or more past user states that are accessible to the computing system. The computing system selects a future user state of the user based on a calculated probability of a possible future user state. The possible future user state is calculated based on the current mobile-device usage and the past user states. For each past user states, a weight based on a time delay factor is used. Based on the selected future user state, the operation of a mobile device of the user is adapted at the future time corresponding to the future user state.

PRIORITY

This application is a continuation under 35 U.S.C. § 120 of U.S. patentapplication Ser. No. 14/882,739, filed 14 Oct. 2015, which is acontinuation under 35 U.S.C. § 120 of U.S. patent application Ser. No.13/656,531, filed 19 Oct. 2012, issued as U.S. Pat. No. 9,219,668.

TECHNICAL FIELD

This disclosure generally relates to mobile devices and mobile deviceusers.

BACKGROUND

A mobile device—such as a smartphone, tablet computer, or laptopcomputer—may include functionality for determining its location,direction, or orientation, such as a Global Positioning System (GPS)receiver, compass, or gyroscope. Such a device may also includefunctionality for wireless communication, such as BLUETOOTHcommunication, near-field communication (NFC), or infrared (IR)communication or communication with a wireless local area networks(WLANs) or cellular-telephone network. Such a device may also includeone or more cameras, scanners, touchscreens, microphones, or speakers.Mobile devices may also execute software applications, such as games,web browsers, or social-networking applications. With social-networkingapplications, users may connect, communicate, and share information withother users in their social networks.

SUMMARY OF PARTICULAR EMBODIMENTS

Particular embodiments enable a mobile device to predict a future stateof a user of that mobile device. In practice, a mobile device logsinformation such as the local time reported by the device, the locationof the device, or the network connectivity of the device andcross-references that information against historical data to predict afuture state of the user of the device. In one embodiment, the mobiledevice user is a user of a social network and the historical data isdrawn from that user's social graph data. Based on a predicted futureuser state, the mobile device alters its behavior to better meet thefuture needs or requirements of the user.

In some embodiments, the predicted future user state of the mobiledevice user can be that the user is commuting to work, that the user isat home, that the user is at work, that the user is having dinner withfriends, that the users is in a public social setting, that the user isin a foreign country, or that the user will be connected via aparticular telecommunications network. The mobile device uses thispredicted state to meet the needs of the user. The mobile device maycache new messages until the user has arrived at her predicteddestination. Alternatively, the mobile device may automatically launch asoftware application related to the restaurant the user is dining at. Inparticular embodiments, the mobile device may request lower bandwidthservices while it is predicted to be connected to a particulartelecommunications network. This allows the mobile device toautomatically tailor operation to the user's activities.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example network environment associated with asocial-networking system.

FIG. 2 illustrates an example mobile device.

FIG. 3 illustrates an example method of predicting a future state of amobile device user.

FIG. 4 illustrates an example block diagram of a predictor function.

FIG. 5 illustrates an example computer system.

DESCRIPTION OF EXAMPLE EMBODIMENTS

FIG. 1 illustrates an example network environment 100 associated with asocial-networking system. Network environment 100 includes a clientsystem 130, a social-networking system 160, and a third-party system 170connected to each other by a network 110. Although FIG. 1 illustrates aparticular arrangement of client system 130, social-networking system160, third-party system 170, and network 110, this disclosurecontemplates any suitable arrangement of client system 130,social-networking system 160, third-party system 170, and network 110.As an example and not by way of limitation, two or more of client system130, social-networking system 160, and third-party system 170 may beconnected to each other directly, bypassing network 110. As anotherexample, two or more of client system 130, social-networking system 160,and third-party system 170 may be physically or logically co-locatedwith each other in whole or in part. Moreover, although FIG. 1illustrates a particular number of client systems 130, social-networkingsystems 160, third-party systems 170, and networks 110, this disclosurecontemplates any suitable number of client systems 130,social-networking systems 160, third-party systems 170, and networks110. As an example and not by way of limitation, network environment 100may include multiple client system 130, social-networking systems 160,third-party systems 170, and networks 110.

This disclosure contemplates any suitable network 110. As an example andnot by way of limitation, one or more portions of network 110 mayinclude an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local area network (LAN), a wireless LAN (WLAN), a widearea network (WAN), a wireless WAN (WWAN), a metropolitan area network(MAN), a portion of the Internet, a portion of the Public SwitchedTelephone Network (PSTN), a cellular telephone network, or a combinationof two or more of these. Network 110 may include one or more networks110.

Links 150 may connect client system 130, social-networking system 160,and third-party system 170 to communication network 110 or to eachother. This disclosure contemplates any suitable links 150. Inparticular embodiments, one or more links 150 include one or morewireline (such as for example Digital Subscriber Line (DSL) or Data OverCable Service Interface Specification (DOCSIS)), wireless (such as forexample Wi-Fi or Worldwide Interoperability for Microwave Access(WiMAX)), or optical (such as for example Synchronous Optical Network(SONET) or Synchronous Digital Hierarchy (SDH)) links. In particularembodiments, one or more links 150 each include an ad hoc network, anintranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, aportion of the Internet, a portion of the PSTN, a cellulartechnology-based network, a satellite communications technology-basednetwork, another link 150, or a combination of two or more such links150. Links 150 need not necessarily be the same throughout networkenvironment 100. One or more first links 150 may differ in one or morerespects from one or more second links 150.

In particular embodiments, client system 130 may be an electronic deviceincluding hardware, software, or embedded logic components or acombination of two or more such components and capable of carrying outthe appropriate functionalities implemented or supported by clientsystem 130. As an example and not by way of limitation, a client system130 may include a computer system such as a desktop computer, notebookor laptop computer, netbook, a tablet computer, e-book reader, GPSdevice, camera, personal digital assistant (PDA), handheld electronicdevice, cellular telephone, smartphone, other suitable electronicdevice, or any suitable combination thereof. This disclosurecontemplates any suitable client systems 130. A client system 130 mayenable a network user at client system 130 to access network 110. Aclient system 130 may enable its user to communicate with other users atother client systems 130.

In particular embodiments, client system 130 may include a web browser132, such as MICROSOFT INTERNET EXPLORER, GOOGLE CHROME or MOZILLAFIREFOX, and may have one or more add-ons, plug-ins, or otherextensions, such as TOOLBAR or YAHOO TOOLBAR. A user at client system130 may enter a Uniform Resource Locator (URL) or other addressdirecting the web browser 132 to a particular server (such as server162, or a server associated with a third-party system 170), and the webbrowser 132 may generate a Hyper Text Transfer Protocol (HTTP) requestand communicate the HTTP request to server. The server may accept theHTTP request and communicate to client system 130 one or more Hyper TextMarkup Language (HTML) files responsive to the HTTP request. Clientsystem 130 may render a webpage based on the HTML files from the serverfor presentation to the user. This disclosure contemplates any suitablewebpage files. As an example and not by way of limitation, webpages mayrender from HTML files, Extensible Hyper Text Markup Language (XHTML)files, or Extensible Markup Language (XML) files, according toparticular needs. Such pages may also execute scripts such as, forexample and without limitation, those written in JAVASCRIPT, JAVA,MICROSOFT SILVERLIGHT, combinations of markup language and scripts suchas AJAX (Asynchronous JAVASCRIPT and XML), and the like. Herein,reference to a webpage encompasses one or more corresponding webpagefiles (which a browser may use to render the webpage) and vice versa,where appropriate.

In particular embodiments, social-networking system 160 may be anetwork-addressable computing system that can host an online socialnetwork. Social-networking system 160 may generate, store, receive, andtransmit social-networking data, such as, for example, user-profiledata, concept-profile data, social-graph information, or other suitabledata related to the online social network. Social-networking system 160may be accessed by the other components of network environment 100either directly or via network 110. In particular embodiments,social-networking system 160 may include one or more servers 162. Eachserver 162 may be a unitary server or a distributed server spanningmultiple computers or multiple datacenters. Servers 162 may be ofvarious types, such as, for example and without limitation, web server,news server, mail server, message server, advertising server, fileserver, application server, exchange server, database server, proxyserver, another server suitable for performing functions or processesdescribed herein, or any combination thereof. In particular embodiments,each server 162 may include hardware, software, or embedded logiccomponents or a combination of two or more such components for carryingout the appropriate functionalities implemented or supported by server162. In particular embodiments, social-networking system 164 may includeone or more data stores 164. Data stores 164 may be used to storevarious types of information. In particular embodiments, the informationstored in data stores 164 may be organized according to specific datastructures. In particular embodiments, each data store 164 may be arelational database. Particular embodiments may provide interfaces thatenable a client system 130, a social-networking system 160, or athird-party system 170 to manage, retrieve, modify, add, or delete, theinformation stored in data store 164.

In particular embodiments, social-networking system 160 may store one ormore social graphs in one or more data stores 164. In particularembodiments, a social graph may include multiple nodes—which may includemultiple user nodes (each corresponding to a particular user) ormultiple concept nodes (each corresponding to a particular concept)—andmultiple edges connecting the nodes. Social-networking system 160 mayprovide users of the online social network the ability to communicateand interact with other users. In particular embodiments, users may jointhe online social network via social-networking system 160 and then addconnections (i.e., relationships) to a number of other users ofsocial-networking system 160 whom they want to be connected to. Herein,the term “friend” may refer to any other user of social-networkingsystem 160 with whom a user has formed a connection, association, orrelationship via social-networking system 160.

In particular embodiments, social-networking system 160 may provideusers with the ability to take actions on various types of items orobjects, supported by social-networking system 160. As an example andnot by way of limitation, the items and objects may include groups orsocial networks to which users of social-networking system 160 maybelong, events or calendar entries in which a user might be interested,computer-based applications that a user may use, transactions that allowusers to buy or sell items via the service, interactions withadvertisements that a user may perform, or other suitable items orobjects. A user may interact with anything that is capable of beingrepresented in social-networking system 160 or by an external system ofthird-party system 170, which is separate from social-networking system160 and coupled to social-networking system 160 via a network 110.

In particular embodiments, social-networking system 160 may be capableof linking a variety of entities. As an example and not by way oflimitation, social-networking system 160 may enable users to interactwith each other as well as receive content from third-party systems 170or other entities, or to allow users to interact with these entitiesthrough an application programming interfaces (API) or othercommunication channels.

In particular embodiments, a third-party system 170 may include one ormore types of servers, one or more data stores, one or more interfaces,including but not limited to APIs, one or more web services, one or morecontent sources, one or more networks, or any other suitable components,e.g., that servers may communicate with. A third-party system 170 may beoperated by a different entity from an entity operatingsocial-networking system 160. In particular embodiments, however,social-networking system 160 and third-party systems 170 may operate inconjunction with each other to provide social-networking services tousers of social-networking system 160 or third-party systems 170. Inthis sense, social-networking system 160 may provide a platform, orbackbone, which other systems, such as third-party systems 170, may useto provide social-networking services and functionality to users acrossthe Internet.

In particular embodiments, a third-party system 170 may include athird-party content object provider. A third-party content objectprovider may include one or more sources of content objects, which maybe communicated to a client system 130. As an example and not by way oflimitation, content objects may include information regarding things oractivities of interest to the user, such as, for example, movie showtimes, movie reviews, restaurant reviews, restaurant menus, productinformation and reviews, or other suitable information. As anotherexample and not by way of limitation, content objects may includeincentive content objects, such as coupons, discount tickets, giftcertificates, or other suitable incentive objects.

In particular embodiments, social-networking system 160 also includesuser-generated content objects, which may enhance a user's interactionswith social-networking system 160. User-generated content may includeanything a user can add, upload, send, or “post” to social-networkingsystem 160. As an example and not by way of limitation, a usercommunicates posts to social-networking system 160 from a client system130. Posts may include data such as status updates or other textualdata, location information, photos, videos, links, music or othersimilar data or media. Content may also be added to social-networkingsystem 160 by a third-party through a “communication channel,” such as anewsfeed or stream.

In particular embodiments, social-networking system 160 may include avariety of servers, sub-systems, programs, modules, logs, and datastores 164. In particular embodiments, social-networking system 160 mayinclude one or more of the following: a web server, action logger,API-request server, relevance-and-ranking engine, content-objectclassifier, notification controller, action log,third-party-content-object-exposure log, inference module,authorization/privacy server, search module, ad-targeting module,user-interface module, user-profile store, connection store, third-partycontent store, or location store. Social-networking system 160 may alsoinclude suitable components such as network interfaces, securitymechanisms, load balancers, failover servers,management-and-network-operations consoles, other suitable components,or any suitable combination thereof. In particular embodiments,social-networking system 160 may include one or more user-profile storesfor storing user profiles. A user profile may include, for example,biographic information, demographic information, behavioral information,social information, or other types of descriptive information, such aswork experience, educational history, hobbies or preferences, interests,affinities, or location. Interest information may include interestsrelated to one or more categories. Categories may be general orspecific. As an example and not by way of limitation, if a user “likes”an article about a brand of shoes the category may be the brand, or thegeneral category of “shoes” or “clothing.” A connection store may beused for storing connection information about users. The connectioninformation may indicate users who have similar or common workexperience, group memberships, hobbies, educational history, or are inany way related or share common attributes. The connection informationmay also include user-defined connections between different users andcontent (both internal and external). A web server may be used forlinking social-networking system 160 to one or more client systems 130or one or more third-party system 170 via network 110. The web servermay include a mail server or other messaging functionality for receivingand routing messages between social-networking system 160 and one ormore client systems 130. An API-request server may allow a third-partysystem 170 to access information from social-networking system 160 bycalling one or more APIs. An action logger may be used to receivecommunications from a web server about a user's actions on or offsocial-networking system 160. In conjunction with the action log, athird-party-content-object log may be maintained of user exposures tothird-party-content objects. A notification controller may provideinformation regarding content objects to a client system 130.Information may be pushed to a client system 130 as notifications, orinformation may be pulled from client system 130 responsive to a requestreceived from client system 130. Authorization servers may be used toenforce one or more privacy settings of the users of social-networkingsystem 160. A privacy setting of a user determines how particularinformation associated with a user can be shared. The authorizationserver may allow users to opt in or opt out of having their actionslogged by social-networking system 160 or shared with other systems(e.g., third-party system 170), such as, for example, by settingappropriate privacy settings. Third-party-content-object stores may beused to store content objects received from third parties, such as athird-party system 170. Location stores may be used for storing locationinformation received from client systems 130 associated with users.Ad-pricing modules may combine social information, the current time,location information, or other suitable information to provide relevantadvertisements, in the form of notifications, to a user.

A geo-social-networking system is a social-networking system in whichgeographic services and capabilities are used to enable additionalsocial interactions. User-submitted location data or geo-locationtechniques (e.g., mobile phone position logging) can allow a geo-socialnetwork to connect and coordinate users with local people or events thatmatch their interests. For example, users can check-in to a place usinga mobile client application by providing a name of a place (or selectinga place from a pre-established list of places). Thegeo-social-networking system, among other things, can record informationabout the user's presence at the place and possibly provide thisinformation to other users of the geo-social-networking system.

A social-networking system 160 may maintain a data store 164 ofinformation relating to geographic locations or places. Places maycorrespond to various physical locations, such as restaurants, bars,businesses, train stations, and airports. A social-networking system 160may allow users to access information regarding each place using aclient application (e.g., a web browser 132) hosted by a client system130, such as a mobile device. In addition to user profile and placeinformation, the social-networking system 160 may log or maintain otherinformation about the user. For example, the social-networking systemmay support geo-social-networking system functionality including one ormore location-based services that record the user's location. Forexample, users may access the geo-social-networking system using aspecial-purpose client application hosted by a client system 130. Theclient system 130 may automatically access GPS, cellular triangulation,or other geo-location functions supported by the client system 130 andreport the user's current location to the geo-social-networking system.A check-in to a given place may occur when a user is physically locatedat a place and, using a client system 130, access thegeo-social-networking system to register the user's presence at theplace. A user may select a place from a list of existing places near tothe user's current location or create a new place. The user may alsoidentify one or more other users in connection with a check-in (such asfriends of a user) and associate them with the check-in as well. Forexample, a record of the user's check-in activity may be stored in adata store 164.

Still further, a special purpose client application hosted on a mobiledevice of a user may be configured to continuously capture location dataof the mobile device and send the location data to the social-networkingsystem. In this manner, the social-networking system may log the user'slocation.

In particular embodiments, a data store 164 associated withsocial-networking system 160 may store an information base of places,where each place includes a name, a geographic location and metainformation (such as the user that initially created the place, check-inactivity data, and the like). For example, a geographic location of anInternet connected computer or computing device can be identified by theassigned Internet Protocol (IP) address. For example, a geographiclocation of a cell phone equipped with cellular, Wi-Fi and/or GPScapabilities can be identified by cell tower triangulation, Wi-Fipositioning, and/or GPS positioning. In particular embodiments, the datastore 164 may store a geographic location and additional information ofa plurality of places. For example, a place can be a local business, apoint of interest (e.g., Union Square in San Francisco, Calif.), acollege, a city, or a national park. For example, a geographic locationof a place (e.g., a local coffee shop) can be an address, a set ofgeographic coordinates (latitude and longitude), or a reference toanother place (e.g., “the coffee shop next to the train station”). Forexample, a geographic location of a place with a large area (e.g.,Yosemite National Park) can be a shape (e.g., a circle, or a polygon)approximating the boundary of the place and/or a centroid of the shape.For example, additional information of a place can be business hours orphotographs of the place. In particular embodiments, thesocial-networking system 160 may calculate one or more routes of a userbased on the user's user profile information, check-in activities,and/or geographic location data reported by a client application (seeabove) and store the one or more routes. For example, thesocial-networking system can calculate a “commute route” of a userbetween the user's home and work by using a mapping service application,or by using geographic location data points from the user's GPS-equippedmobile phone while the user is driving to work.

In particular embodiments, a mobile device (e.g., client system 130) mayinclude hardware, firmware, and software. FIG. 2 illustrates an examplemobile-device client system 130. In particular embodiments, clientsystem 130 may be a smart phone (e.g., iPhone or Blackberry), which is amobile telephone that offers more advanced computing ability andconnectivity than a traditional mobile phone. It may be considered as ahandheld computer integrated with a mobile phone. In particularembodiments, client system 130 may be a netbook or tablet computer(e.g., iPad). In particular embodiments, client system 130 may beconnected to a network through a wireless connection.

In particular embodiments, client system 130 may include hardware 210and software 220. In particular embodiments, hardware 210 may includeany number of hardware components such as, for example and withoutlimitation, processor 211, memory 212, storage 213, transceiver 214,input/output device 215 (e.g., display, touch screen, keypad,microphone, speaker, etc.), camera 216, global positioning system (GPS)sensor 217, sensors hub 218, notification control switch 219, radiofrequency identification (RFID) reader 241, radio frequency (RF) sensor242, and so on. This disclosure contemplates any suitable hardwarecomponents. In particular embodiments, some or all of a user's user datamay be stored in storage 213.

In particular embodiments, software 220 may include an operating system221, which may include a kernel 231 and/or any number of device drivers232 corresponding to some of the hardware components available on clientsystem 130. Operating system 221 may be selected for client system 130based on the actual type of device client system 130 is. For example, ifclient system 130 is a mobile device (e.g., a smart phone), thenoperating system 221 may be a mobile operating system such as, forexample and without limitation, Microsoft's Windows Mobile, Google'sAndroid, Nokia's Symbian, Apple's iOS, and Samsung's Bada.

In particular embodiments, one or more software applications 223 may beexecuted on client system 130. In particular embodiments, they may benative applications installed and residing on client system 130. Forexample, one application (e.g., Google Maps) may enable a device user toview a map, search for addresses and businesses, and get directions; asecond application may enable the device user to read, send, and receiveemails; a third application (e.g., a web browser) may enable the deviceuser to browse and search the Internet; a fourth application may enablethe device user to take photos or record videos using camera 216; afifth application may allow the device user to receive and initiate VoIPand/or cellular network calls, and so on. In particular embodiments,there may be a software application (e.g., notification control 241)that enables the device user to manage the notifications pushed toclient system 130. Notification control 241 is described in more detailbelow. Each software application 220 may have a user interface and mayimplement one or more specific functionalities. Each softwareapplication 220 may include one or more software modules implementingthe individual functionalities. The executable code of softwareapplications 220, including notification control 241, may be stored in acomputer-readable and non-transitory medium (e.g., storage 213 or memory212) on mobile device 130.

FIG. 3 illustrates an example method for predicting the future userstate of a user of a mobile device. The method may start at step 310,where the system accesses data associated with a mobile-computing-device(e.g., client system 130) usage by a user. In particular embodiments,this data may be stored by the social-networking system 160. Inparticular embodiments, this data may be a unique identifier of theclient system 130 or a unique identifier of an application on the clientsystem 130. In particular embodiments, this data may be the InternetProtocol (IP) address of the client system 130. In particularembodiments, this data may be the local time reported by the clientsystem 130. In particular embodiments this data may be the currentlocation or a vector of movement of the client system 130. The locationand the vector of movement can be determined via GPS, assisted GPS,cellular triangulation, or any other suitable manner of obtaining thelocation or vector of movement.

At step 320, the system accesses data associated with the past userstates of the user. The past user state may be a temporal, spatial,modal, or social accessibility of the user. In particular embodiments,this data may be stored by the social-networking system 160. Inparticular embodiments, a past user state may be commuting to and fromthe user's place of employment. This state would have temporal, spatial,modal, and social aspects relevant to the user. In particularembodiments, the past user state may be attending an event stored by thesocial-networking system 160. In particular embodiments, the past userstate may be traveling in a geographic area connected to informationstored by the social-networking system 160. For instance, the user mayhave posted a status update indicating that the user was on vacation ata time proximate to the user's mobile computing device indicating alocation in Hawaii. In particular embodiments, the past user state maybe determined from data associated with one of the user's contactsstored by the social-networking system 160. For instance, the user'scontact may have previously saved check-in activity data indicating theuser and a location. In particular embodiments, the past user state maybe connected to the client system 130 currently in use by the user. Forinstance, the past user state may be that the user was in transit at atime proximate to a received unique client-system identifier indicatingthat the client system 130 is an in-car navigation unit. As anotherexample, the past user state may be that the user was “working” when theclient system 130 was a specific laptop, or that the user was “busy”when the client system 130 was a mobile gaming device.

At step 330, the system predicts a future user state and future clientsystem 130 usage by the user at a future time. In particular embodimentsthe social-networking system 160 may use a number of geo-social factors.For example, the social-networking system 160 may have developed adataset of connected user states and client system usage data points bycross-referencing stored data. The social-networking system 160 may alsohave access to current time or location data for the client system 130.Additionally, the social-networking system 160 may also have stored dataconcerning future events and calendar appointments of the user. Thesocial-networking system 160 may use one or more of the data accessed insteps 310 and 320 to algorithmically predict future user states.

In particular embodiments, the system may use regression analysis onsome or all of the data accessed in steps 310 or 320 to predict thefuture user state. In particular embodiments, the system may use alinear regression of multiple independent variables to assignprobabilities to a number of possible states. An exemplar linearregression may be y_(i)=β₁X_(i1)+β₂X_(i2)+ . . . +β_(p)X_(ip) whereiny_(i) represents a possible future state chosen from a set of past userstates accessed in step 320, x_(in) represents an independent variable,β_(in) represents a weighting factor to be assigned to each variable,and where n spans the values 1 to p. In a particular embodiment, theindependent variables may be any of the types of data discussed above inconnection with step 310.

In particular embodiments, the system may use a decision-tree analysison some or all of the data accessed in steps 310 or 320 to predict thefuture user state. The system may use historical data to developdecision nodes and chance nodes of the decision tree to predict futureuser states. For example, based on historical data, a certaincombination of inputs may predict a user state. If the future local timecorresponds with past local times associated with the past user state of“commuting”, the current reported client system 130 is an in-carnavigation unit, and the current reported location of the client system130 is on the known commuting path for the user, the system may workthrough a decision tree to determine that the future user state of theuser is commuting to work for a given time period. In particularembodiments, the decision-tree analysis may be desirable in a systemwith a small number of potential future user states. In particularembodiments the decision-tree analysis may be combined with otherprediction techniques.

In particular embodiments, the system may use a neural-network analysison some or all of the data accessed in steps 310 or 320 to predict thefuture user state. For example, the system may implement a supervisedlearning neural network to find a function mapping input variables drawnfrom the data accessed in step 310 to user-states drawn from the dataaccessed in step 320. The neural-networking analysis may try to minimizethe mean-squared error between the network's predicted user state andknown past user states. By minimizing this error, the network is able todevelop an approximated function for predicting future user states.

In particular embodiments, the system may use an expert-system analysison some or all of the data accessed in steps 310 or 320 to predict thefuture user state. The system may build a knowledge base of the expertsystem based on historic data. For example, the system may develop arule that “IF the client system 130 is Laptop001 THEN user is at work”.As another example, the system may develop a rule that “IF the currentlocation is Hawaii THEN the user is on vacation”. As another example,the system may develop a rule that “IF the current local time is between7 PM and 6 AM THEN the user is at home”. By developing said knowledgebase, the system may then run input variables through the expert-systeminference engine either in batches or serially to predict future userstates.

This disclosure contemplates any suitable manner of predicting a futureuser state and utilizing any combination of factors accessed in steps310 and 320 or weighting of factors in the calculation of the predictedfuture user state.

At step 340, the system adapts the operation of the client system 130 ofthe user at a future time in response to the predicted future userstate, at which point the method may end. In particular embodiments, thepredicted user state may be that the user will be travelling in ageographic area. The system may adapt by pushing data relevant to thegeographic area to the client system 130. For example, if the predicteduser state is that the user will be vacationing in Hawaii, the systemcan push relevant data (e.g. weather information, travel advisories,restaurant reviews, and taxi cab advertisements) to the client system130. Some or all of the data can be displayed as notifications to theuser. Alternatively, some or all of the data can be cached on the clientsystem 130 and used to pre-populate suggested searches and suggestedresults, or reduce future data usage by the client system 130.

In particular embodiments, the system for predicting a future state of amobile device user as illustrated in FIG. 3 may be associated with asocial-networking system 160. In this case, the social-networking systemmay implement the method illustrated in FIG. 3 (e.g., as computersoftware) and use the method to predict the future user state of userswho are also members of the social-networking system 160.

It may be desirable for a social-networking application on the clientsystem 130 to change its operation in response to the predicted user'sstate. In particular embodiments, the system adapts the operation of theclient system 130 by modifying the logical operation of asocial-networking application on the client system 130. For example, ifthe predicted future user state is that the user is unavailable (e.g. onan airline flight, working, watching a film) then the social-networkingapplication on the user's client system 130 can be set to queue allnotifications to the user until the predicted future user state changes.As further example, if the predicted future user state is that the userwill be out at a public social setting (e.g. attending a birthdayparty), the social networking application on the user's client system130 can be set to launch a camera application when accessed.

In particular embodiments, the system adapts the operation of the clientsystem 130 by altering the characteristics of the data requested by theclient system 130 and sent by the social-networking system 160. Inparticular embodiments, it may be desirable for the social-networkingsystem 160 to provide lower bandwidth services to the client system 130when that device is connected via certain types of links 150. Forexample, some telecommunications providers offer data download limitsand impose fees for exceeding those limits. As another example, sometelecommunications contracts charge increased fees for data transferwhen travelling in a foreign country. If the predicted future user stateindicates that the client system 130 will be connected via a link 150associated with a data limit or increased fees, the social-networkingsystem 160 may transmit lower bandwidth content. In particularembodiments, it may be desirable to increase an interval at which thesocial-networking system 160 polls the client system 130 to determinethe device's location. For example, if the predicted future user stateis that the user will be at home, the social-networking system 160 mayadapt by increasing the polling interval to once every hour. Byincreasing the polling interval, it may be possible for thesocial-networking system 160 to increase the battery life of the clientsystem 130.

Particular embodiments may repeat the steps of the method of FIG. 3,where appropriate. Moreover, although this disclosure describes andillustrates particular steps of the method of FIG. 3 as occurring in aparticular order, this disclosure contemplates any suitable steps of themethod of FIG. 3 occurring in any suitable order. Furthermore, althoughthis disclosure describes and illustrates particular components,devices, or systems carrying out particular steps of the method of FIG.3, this disclosure contemplates any suitable combination of any suitablecomponents, devices, or systems carrying out any suitable steps of themethod of FIG. 3.

FIG. 4 is a block diagram of an example function for predicting thefuture user state. To predict a future user state 415, weights 405 areapplied to predictor functions 410 and then combined to obtain apredicted future user state 415. Although FIG. 4 shows three predictorfunctions 410, any number of predictor functions can be employed inother embodiments of the invention. Additionally, in the embodiment ofFIG. 4, the weighted predictor functions 410 are combined linearly. Indifferent embodiments, other forms of combination may be used, includingharmonic means, mean squares, and geometric means. Additionally,multiple predicted future user states 415 with varying weights 405 maybe computed before adapting the operation of the client system 130 asdescribed in method step 340.

The system may comprise one or more predictor modules (e.g., anapplication) that are responsible for computing a set predictorfunction, which predicts a future user state. As discussed above, eachpredictor function may be any suitable method for predicting a futureuser state. In some embodiments, the predictor function may be generatedusing a machine learned algorithm that is trained using a user'shistorical activity associated with a specific user state. Machinelearning is a scientific discipline that is concerned with the designand development of algorithms that allow computers to learn based ondata. The computational analysis of machine learning algorithms andtheir performance is a branch of theoretical computer science known ascomputational learning theory. The desired goal is to improve thealgorithms through experience (e.g., by applying the data to thealgorithms in order to “train” the algorithms). The data are thus oftenreferred to as “training data”. Each predictor module thus provides apredictor function for each of a set of possible future user states,where a predictor function may take as an input some or all of the dataaccessed in method step 310 and then outputs a measure of the likelihoodthat the user will have a predicted future user state.

In some embodiments, one or more of the predictor functions may use adecay factor in which the strength of the signal from a user'shistorical activity decays with time. Moreover, different predictorfunctions may decay the historical activity at different rates. Forexample, some types of predicted future user state, like commuting towork, indicate a more persistent connection than other types of activitythat indicate a more ephemeral connection, like attending anon-recurring event (e.g. a wedding). Therefore, the predictor functionsmay decay the effect of historical activity based on an understandingabout how that past user state may become less relevant over the passageof time. Various decay mechanisms may be used for this purpose. Forexample, a predictor function may use a mathematical function, such asan exponential decay, to decay the statistics about a predicted userstate. In another embodiment, the decay is implemented by selecting onlythose statistics about a user state that occurred within a specificwindow of time, such as 24 hours or 30 days.

FIG. 5 illustrates an example computer system 500. In particularembodiments, one or more computer systems 500 perform one or more stepsof one or more methods described or illustrated herein. In particularembodiments, one or more computer systems 500 provide functionalitydescribed or illustrated herein. In particular embodiments, softwarerunning on one or more computer systems 500 performs one or more stepsof one or more methods described or illustrated herein or providesfunctionality described or illustrated herein. Particular embodimentsinclude one or more portions of one or more computer systems 500.Herein, reference to a computer system may encompass a computing device,where appropriate. Moreover, reference to a computer system mayencompass one or more computer systems, where appropriate.

This disclosure contemplates any suitable number of computer systems500. This disclosure contemplates computer system 500 taking anysuitable physical form. As example and not by way of limitation,computer system 500 may be an embedded computer system, a system-on-chip(SOC), a single-board computer system (SBC) (such as, for example, acomputer-on-module (COM) or system-on-module (SOM)), a desktop computersystem, a laptop or notebook computer system, an interactive kiosk, amainframe, a mesh of computer systems, a mobile telephone, a personaldigital assistant (PDA), a server, a tablet computer system, or acombination of two or more of these. Where appropriate, computer system500 may include one or more computer systems 500; be unitary ordistributed; span multiple locations; span multiple machines; spanmultiple data centers; or reside in a cloud, which may include one ormore cloud components in one or more networks. Where appropriate, one ormore computer systems 500 may perform without substantial spatial ortemporal limitation one or more steps of one or more methods describedor illustrated herein. As an example and not by way of limitation, oneor more computer systems 500 may perform in real time or in batch modeone or more steps of one or more methods described or illustratedherein. One or more computer systems 500 may perform at different timesor at different locations one or more steps of one or more methodsdescribed or illustrated herein, where appropriate.

In particular embodiments, computer system 500 includes a processor 502,memory 504, storage 506, an input/output (I/O) interface 508, acommunication interface 510, and a bus 512. Although this disclosuredescribes and illustrates a particular computer system having aparticular number of particular components in a particular arrangement,this disclosure contemplates any suitable computer system having anysuitable number of any suitable components in any suitable arrangement.

In particular embodiments, processor 502 includes hardware for executinginstructions, such as those making up a computer program. As an exampleand not by way of limitation, to execute instructions, processor 502 mayretrieve (or fetch) the instructions from an internal register, aninternal cache, memory 504, or storage 506; decode and execute them; andthen write one or more results to an internal register, an internalcache, memory 504, or storage 506. In particular embodiments, processor502 may include one or more internal caches for data, instructions, oraddresses. This disclosure contemplates processor 502 including anysuitable number of any suitable internal caches, where appropriate. Asan example and not by way of limitation, processor 502 may include oneor more instruction caches, one or more data caches, and one or moretranslation lookaside buffers (TLBs). Instructions in the instructioncaches may be copies of instructions in memory 504 or storage 506, andthe instruction caches may speed up retrieval of those instructions byprocessor 502. Data in the data caches may be copies of data in memory504 or storage 506 for instructions executing at processor 502 tooperate on; the results of previous instructions executed at processor502 for access by subsequent instructions executing at processor 502 orfor writing to memory 504 or storage 506; or other suitable data. Thedata caches may speed up read or write operations by processor 502. TheTLBs may speed up virtual-address translation for processor 502. Inparticular embodiments, processor 502 may include one or more internalregisters for data, instructions, or addresses. This disclosurecontemplates processor 502 including any suitable number of any suitableinternal registers, where appropriate. Where appropriate, processor 502may include one or more arithmetic logic units (ALUs); be a multi-coreprocessor; or include one or more processors 502. Although thisdisclosure describes and illustrates a particular processor, thisdisclosure contemplates any suitable processor.

In particular embodiments, memory 504 includes main memory for storinginstructions for processor 502 to execute or data for processor 502 tooperate on. As an example and not by way of limitation, computer system500 may load instructions from storage 506 or another source (such as,for example, another computer system 500) to memory 504. Processor 502may then load the instructions from memory 504 to an internal registeror internal cache. To execute the instructions, processor 502 mayretrieve the instructions from the internal register or internal cacheand decode them. During or after execution of the instructions,processor 502 may write one or more results (which may be intermediateor final results) to the internal register or internal cache. Processor502 may then write one or more of those results to memory 504. Inparticular embodiments, processor 502 executes only instructions in oneor more internal registers or internal caches or in memory 504 (asopposed to storage 506 or elsewhere) and operates only on data in one ormore internal registers or internal caches or in memory 504 (as opposedto storage 506 or elsewhere). One or more memory buses (which may eachinclude an address bus and a data bus) may couple processor 502 tomemory 504. Bus 512 may include one or more memory buses, as describedbelow. In particular embodiments, one or more memory management units(MMUs) reside between processor 502 and memory 504 and facilitateaccesses to memory 504 requested by processor 502. In particularembodiments, memory 504 includes random access memory (RAM). This RAMmay be volatile memory, where appropriate Where appropriate, this RAMmay be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, whereappropriate, this RAM may be single-ported or multi-ported RAM. Thisdisclosure contemplates any suitable RAM. Memory 504 may include one ormore memories 504, where appropriate. Although this disclosure describesand illustrates particular memory, this disclosure contemplates anysuitable memory.

In particular embodiments, storage 506 includes mass storage for data orinstructions. As an example and not by way of limitation, storage 506may include a hard disk drive (HDD), a floppy disk drive, flash memory,an optical disc, a magneto-optical disc, magnetic tape, or a UniversalSerial Bus (USB) drive or a combination of two or more of these. Storage506 may include removable or non-removable (or fixed) media, whereappropriate. Storage 506 may be internal or external to computer system500, where appropriate. In particular embodiments, storage 506 isnon-volatile, solid-state memory. In particular embodiments, storage 506includes read-only memory (ROM). Where appropriate, this ROM may bemask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM),electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM),or flash memory or a combination of two or more of these. Thisdisclosure contemplates mass storage 506 taking any suitable physicalform. Storage 506 may include one or more storage control unitsfacilitating communication between processor 502 and storage 506, whereappropriate. Where appropriate, storage 506 may include one or morestorages 506. Although this disclosure describes and illustratesparticular storage, this disclosure contemplates any suitable storage.

In particular embodiments, I/O interface 508 includes hardware,software, or both providing one or more interfaces for communicationbetween computer system 500 and one or more I/O devices. Computer system500 may include one or more of these I/O devices, where appropriate. Oneor more of these I/O devices may enable communication between a personand computer system 500. As an example and not by way of limitation, anI/O device may include a keyboard, keypad, microphone, monitor, mouse,printer, scanner, speaker, still camera, stylus, tablet, touch screen,trackball, video camera, another suitable I/O device or a combination oftwo or more of these. An I/O device may include one or more sensors.This disclosure contemplates any suitable I/O devices and any suitableI/O interfaces 508 for them. Where appropriate, I/O interface 508 mayinclude one or more device or software drivers enabling processor 502 todrive one or more of these I/O devices. I/O interface 508 may includeone or more I/O interfaces 508, where appropriate. Although thisdisclosure describes and illustrates a particular I/O interface, thisdisclosure contemplates any suitable I/O interface.

In particular embodiments, communication interface 510 includeshardware, software, or both providing one or more interfaces forcommunication (such as, for example, packet-based communication) betweencomputer system 500 and one or more other computer systems 500 or one ormore networks. As an example and not by way of limitation, communicationinterface 510 may include a network interface controller (NIC) ornetwork adapter for communicating with an Ethernet or other wire-basednetwork or a wireless NIC (WNIC) or wireless adapter for communicatingwith a wireless network, such as a WI-FI network. This disclosurecontemplates any suitable network and any suitable communicationinterface 510 for it. As an example and not by way of limitation,computer system 500 may communicate with an ad hoc network, a personalarea network (PAN), a local area network (LAN), a wide area network(WAN), a metropolitan area network (MAN), or one or more portions of theInternet or a combination of two or more of these. One or more portionsof one or more of these networks may be wired or wireless. As anexample, computer system 500 may communicate with a wireless PAN (WPAN)(such as, for example, a BLUETOOTH WPAN), a WI-FI network, a WI-MAXnetwork, a cellular telephone network (such as, for example, a GlobalSystem for Mobile Communications (GSM) network), or other suitablewireless network or a combination of two or more of these. Computersystem 500 may include any suitable communication interface 510 for anyof these networks, where appropriate. Communication interface 510 mayinclude one or more communication interfaces 510, where appropriate.Although this disclosure describes and illustrates a particularcommunication interface, this disclosure contemplates any suitablecommunication interface.

In particular embodiments, bus 512 includes hardware, software, or bothcoupling components of computer system 500 to each other. As an exampleand not by way of limitation, bus 512 may include an AcceleratedGraphics Port (AGP) or other graphics bus, an Enhanced Industry StandardArchitecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT)interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBANDinterconnect, a low-pin-count (LPC) bus, a memory bus, a Micro ChannelArchitecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, aPCI-Express (PCIe) bus, a serial advanced technology attachment (SATA)bus, a Video Electronics Standards Association local (VLB) bus, oranother suitable bus or a combination of two or more of these. Bus 512may include one or more buses 512, where appropriate. Although thisdisclosure describes and illustrates a particular bus, this disclosurecontemplates any suitable bus or interconnect.

Herein, a computer-readable non-transitory storage medium or media mayinclude one or more semiconductor-based or other integrated circuits(ICs) (such, as for example, field-programmable gate arrays (FPGAs) orapplication-specific ICs (ASICs)), hard disk drives (HDDs), hybrid harddrives (HHDs), optical discs, optical disc drives (ODDs),magneto-optical discs, magneto-optical drives, floppy diskettes, floppydisk drives (FDDs), magnetic tapes, solid-state drives (SSDs),RAM-drives, SECURE DIGITAL cards or drives, any other suitablecomputer-readable non-transitory storage media, or any suitablecombination of two or more of these, where appropriate. Acomputer-readable non-transitory storage medium may be volatile,non-volatile, or a combination of volatile and non-volatile, whereappropriate.

Herein, “or” is inclusive and not exclusive, unless expressly indicatedotherwise or indicated otherwise by context. Therefore, herein, “A or B”means “A, B, or both,” unless expressly indicated otherwise or indicatedotherwise by context. Moreover, “and” is both joint and several, unlessexpressly indicated otherwise or indicated otherwise by context.Therefore, herein, “A and B” means “A and B, jointly or severally,”unless expressly indicated otherwise or indicated otherwise by context.

The scope of this disclosure encompasses all changes, substitutions,variations, alterations, and modifications to the example embodimentsdescribed or illustrated herein that a person having ordinary skill inthe art would comprehend. The scope of this disclosure is not limited tothe example embodiments described or illustrated herein. Moreover,although this disclosure describes and illustrates respectiveembodiments herein as including particular components, elements,functions, operations, or steps, any of these embodiments may includeany combination or permutation of any of the components, elements,functions, operations, or steps described or illustrated anywhere hereinthat a person having ordinary skill in the art would comprehend.Furthermore, reference in the appended claims to an apparatus or systemor a component of an apparatus or system being adapted to, arranged to,capable of, configured to, enabled to, operable to, or operative toperform a particular function encompasses that apparatus, system,component, whether or not it or that particular function is activated,turned on, or unlocked, as long as that apparatus, system, or componentis so adapted, arranged, capable, configured, enabled, operable, oroperative.

What is claimed is:
 1. A method comprising: by one or more computingdevices, selecting a future user state of a user based on a weighted setof predictor functions, wherein: each predictor function comprises amachine-learned algorithm trained for a particular possible future userstate based on a current user state of the user and one or more pastuser states of the user, wherein the current user states and past userstates are received from a first mobile device of the user; theselecting the future user state is based on calculated probabilities ofpossible future user states determined by the weighted set of predictorfunctions; and each of the one or more past user states are weighted bya time decay factor, wherein the time decay factor for a particular pastuser state changes value based on an age of the particular past userstate; and by the one or more computing devices, adapting, at a futuretime corresponding to the selected future user state, the operation of asecond mobile device of the user.
 2. The method of claim 1, whereinselecting the future user state is determined by a combination of theweighted set of predictor functions, wherein the combination isdetermined: linearly; as a harmonic mean of the weighted set ofpredictor functions; as mean squares of the weighted set of predictorfunctions; or as a geometric mean of the weighted set of predictorfunctions.
 3. The method of claim 1, wherein the selected future userstate is associated with the user traveling within a geographical area.4. The method of claim 1, wherein the past user states of the usercomprise one or more of temporal, spatial, modal, or socialaccessibility of the user.
 5. The method of claim 1, wherein the firstmobile device and the second mobile device are the same device.
 6. Themethod of claim 1, wherein the selected future user state is associatedwith a future mobile-device usage by the user.
 7. The method of claim 6,wherein adapting the operation of the mobile device of the user furthercomprises adapting network interaction with the second mobile device atthe future time to the future mobile-computing-device usage.
 8. Themethod of claim 1, wherein adapting the operation of the mobile devicecomprises modifying the interaction of a telecommunications network withthe second mobile device to provide wireless connectivity to the mobiledevice.
 9. The method of claim 1, wherein the adapting the operation ofthe mobile device of the user comprises adapting network interactionwith the second mobile device, the adapting comprising automaticallyselecting social-networking information to push to the second mobiledevice, wherein the social-networking information is relevant to theselected future user state.
 10. The method of claim 1, wherein: the useris a user of a social-networking system; and adapting the operation ofthe second mobile device comprises requesting interaction by the secondmobile device with the social-networking system.
 11. The method of claim10, wherein: the future user state of the user comprises the usertraveling within a geographical area at the future time; and requestinginteraction by the second mobile device with the social-networkingsystem comprises automatically selecting social-networking informationto push to the second mobile device relevant to the user travelingwithin the geographical area.
 12. The method of claim 10, wherein: thefuture user state of the user comprises a location and an activity ofthe user; and requesting interaction by the second mobile device withthe social-networking system comprises modifying one or more logicaloperations of a social-networking application on the second mobiledevice relevant to the location and activity of the user for access bythe user at the future time.
 13. The method of claim 1, wherein: thefuture user state of the user comprises the user commuting; and adaptingthe operation of the second mobile device comprises requesting contentwith lower bandwidth requirements for transmission to the second mobiledevice while the user is commuting.
 14. The method of claim 1, wherein:the future user state of the user comprises a location of the user; andadapting the operation of the second mobile device comprises reducingpolling of the second mobile device for its geographic location.
 15. Themethod of claim 1, wherein the future time is proximate to a currenttime.
 16. The method of claim 1, wherein the current user statecomprises one or more of: an identifier of the mobile device; anidentifier of an application on the mobile device; an Internet Protocol(IP) address of the mobile device; a location of the mobile device; avector of movement of the mobile device; or a local time reported by themobile device.
 17. The method of claim 1, wherein: the user is a user ofa social-networking system, the social-networking system comprising agraph that comprises a plurality of nodes and a plurality of edgesconnecting the nodes, at least one node in the graph corresponding tothe user; and the past user states comprise social-networkinginformation from the graph associated with the user.
 18. The method ofclaim 1, wherein predicting the future user state of the user comprisesone or more of: regression analysis of the current user state or thepast user states; decision-tree analysis of the current user state orthe past user states; neural-network analysis of the current user stateor the past user states; or expert-system analysis of the current userstate or the past user states.
 19. The method of claim 1, wherein theprocessors are further operable when executing the instructions to:receive an indication of the current user state, wherein the currentuser state comprises a current mobile-device usage by the user; andaccess information about the one or more past user states of the user.20. One or more computer-readable non-transitory storage media embodyingsoftware that is operable when executed to: select a future user stateof the a user based on a weighted set of predictor functions, wherein:each predictor function comprises a machine-learned algorithm trainedfor a particular possible future user state based on a current userstate of the user and one or more past user states of the user, whereinthe current user states and past user states are received from a firstmobile device of the user; the selecting the future user state is basedon calculated probabilities of possible future user states determined bythe weighted set of predictor functions; and each of the one or morepast user states are weighted by a time decay factor, wherein the timedecay factor for a particular past user state changes value based on anage of the particular past user state; and adapt, at a future timecorresponding to the selected future user state, the operation of asecond mobile device of the user.
 21. A system comprising: one or moreprocessors; and a memory coupled to the processors comprisinginstructions executable by the processors, the processors operable whenexecuting the instructions to: select a future user state of the a userbased on a weighted set of predictor functions, wherein: each predictorfunction comprises a machine-learned algorithm trained for a particularpossible future user state based on a current user state of the user andone or more past user states of the user, wherein the current userstates and past user states are received from a first mobile device ofthe user; the selecting the future user state is based on calculatedprobabilities of possible future user states determined by the weightedset of predictor functions; and each of the one or more past user statesare weighted by a time decay factor, wherein the time decay factor for aparticular past user state changes value based on an age of theparticular past user state; and adapt, at a future time corresponding tothe selected future user state, the operation of a second mobile deviceof the user.
 22. The system of claim 21, wherein selecting the futureuser state is determined by a combination of the weighted set ofpredictor functions, wherein the combination is determined: linearly; asa harmonic mean of the weighted set of predictor functions; as meansquares of the weighted set of predictor functions; or as a geometricmean of the weighted set of predictor functions.
 23. The system of claim21, wherein the selected future user state is associated with the usertraveling within a geographical area.
 24. The system of claim 21,wherein the past user states of the user comprise one or more oftemporal, spatial, modal, or social accessibility of the user.
 25. Thesystem of claim 21, wherein the first mobile device and the secondmobile device are the same device.
 26. The system of claim 21, whereinthe selected future user state is associated with a future mobile-deviceusage by the user.
 27. The system of claim 26, wherein adapting theoperation of the mobile device of the user further comprises adaptingnetwork interaction with the second mobile device at the future time tothe future mobile-computing-device usage.
 28. The system of claim 21,wherein adapting the operation of the mobile device comprises modifyingthe interaction of a telecommunications network with the second mobiledevice to provide wireless connectivity to the mobile device.
 29. Thesystem of claim 21, wherein the adapting the operation of the mobiledevice of the user comprises adapting network interaction with thesecond mobile device, the adapting comprising automatically selectingsocial-networking information to push to the second mobile device,wherein the social-networking information is relevant to the selectedfuture user state.
 30. The system of claim 21, wherein: the user is auser of a social-networking system; and adapting the operation of thesecond mobile device comprises requesting interaction by the secondmobile device with the social-networking system.
 31. The system of claim30, wherein: the future user state of the user comprises the usertraveling within a geographical area at the future time; and requestinginteraction by the second mobile device with the social-networkingsystem comprises automatically selecting social-networking informationto push to the second mobile device relevant to the user travelingwithin the geographical area.
 32. The system of claim 30, wherein: thefuture user state of the user comprises a location and an activity ofthe user; and requesting interaction by the second mobile device withthe social-networking system comprises modifying one or more logicaloperations of a social-networking application on the second mobiledevice relevant to the location and activity of the user for access bythe user at the future time.
 33. The system of claim 21, wherein: thefuture user state of the user comprises the user commuting; and adaptingthe operation of the second mobile device comprises requesting contentwith lower bandwidth requirements for transmission to the second mobiledevice while the user is commuting.
 34. The system of claim 21, wherein:the future user state of the user comprises a location of the user; andadapting the operation of the second mobile device comprises reducingpolling of the second mobile device for its geographic location.
 35. Thesystem of claim 21, wherein the future time is proximate to a currenttime.
 36. The system of claim 21, wherein the current user statecomprises one or more of: an identifier of the mobile device; anidentifier of an application on the mobile device; an Internet Protocol(IP) address of the mobile device; a location of the mobile device; avector of movement of the mobile device; or a local time reported by themobile device.
 37. The system of claim 21, wherein: the user is a userof a social-networking system, the social-networking system comprising agraph that comprises a plurality of nodes and a plurality of edgesconnecting the nodes, at least one node in the graph corresponding tothe user; and the past user states comprise social-networkinginformation from the graph associated with the user.